{"id":"W2091564622","doi":"10.1007/s10846-013-9895-6","title":"3D Path Planning for Multiple UAVs for Maximum Information Collection","year":2013,"lang":"en","type":"article","venue":"Journal of Intelligent & Robotic Systems","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":65,"is_retracted":false,"has_abstract":false,"ca_institutions":"Apollo Microwaves (Canada)","funders":"","keywords":"Travelling salesman problem; Autopilot; Motion planning; Path (computing); Genetic algorithm; Mathematical optimization; Population; Computer science; MATLAB; Algorithm; Mathematics; Engineering; Artificial intelligence; Control engineering; Robot","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003320616,0.0007639243,0.0006579204,0.0005678494,0.000817065,0.0006689226,0.0007531823,0.0007461044,0.002213489],"category_scores_gemma":[0.001153622,0.0007713226,0.0007999326,0.0007013511,0.0004002011,0.0008613052,0.001466388,0.0007907584,0.0004005196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007729027,"about_ca_system_score_gemma":0.001191105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006790176,"about_ca_topic_score_gemma":0.009445208,"domain_scores_codex":[0.9996985,0.00005927808,0.00001407183,0.0000748254,0.0001109242,0.00004243538],"domain_scores_gemma":[0.9996697,0.000132367,0.00004521877,0.00005626263,0.00006755521,0.00002893049],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001934566,0.00004675208,0.001063177,0.0001061443,0.00006319761,0.0002421058,0.0002259284,0.8670751,0.01594213,0.005998699,0.002203465,0.1068399],"study_design_scores_gemma":[0.00001042636,0.00003759742,0.0002858427,0.000008104943,0.000007249417,0.00005572112,0.0000320046,0.9932551,0.002515651,0.002830968,0.0009525963,0.000008653675],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03480778,0.000223636,0.961014,0.0001812006,0.00004486091,0.00006221819,0.0001360613,0.0005490247,0.00298122],"genre_scores_gemma":[0.5503073,0.0001508749,0.446913,0.0000446401,0.00001423679,0.0001600002,0.0002466929,0.00007488517,0.002088349],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006790176,"threshold_uncertainty_score":0.01350135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.031584192388562,"score_gpt":0.2640827574055044,"score_spread":0.2324985650169424,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}